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Plot transect/cruise data

This guide follows the basic plotting guide and its goal is to plot data related to oceanographic observations from cruise expeditions. In this walkthrough, we will 1. Create a ficitious cruise track with profile data 2. Plot transects 3. Other plots

As in the basic plotting guide, throughout this guide we will use the OCIM1 grid and we will create a dummy modelled tracer.

using AIBECS, Plots
grd, _ = OCIM1.load()
fdummy(lat, lon, depth) = @. cosd(lat) * sind(lon) + sqrt(depth) / 30
dummy = fdummy(latlondepthvecs(grd)...)
200160-element Array{Float64,1}:
 0.1473082733354871 
 0.14787520507677585
 0.1484347616170568 
 0.1489862761222264 
 0.14952909134202647
 0.15006256039330151
 0.15058604753090166
 0.1510989289053123 
 0.15160059330610717
 0.15209044289033943
 ⋮                  
 1.6980361819651808 
 1.7122377786002079 
 1.6892943789530048 
 1.7014040612198955 
 1.7144142254394876 
 1.7283093671532161 
 1.7071617918226947 
 1.718989643381758  
 1.7316970198229305

A fictitious cruise

For cruise data we use the OceanographyCruises.jl package.

Note

The purpose of the OceanographyCruises.jl package is to provide a Julia interface for handling discrete data from cruises. One goal is to use it for, e.g., GEOTRACES data. However here we merely use it to create fictitious cruise data.

Let us create a station Sydney at (34°S, 152°E) and a ALOHA station at (22.75°N, 158°W).

using OceanographyCruises
Sydney = Station(name="Sydney", lat=-30, lon=156)
ALOHA = Station(name="ALOHA", lat=22.75, lon=-158)
Station ALOHA (22.8N, 158.0W)

Now let's create a range of 10 stations from Sydney to ALOHA.

Nstations = 10
stations = range(Sydney, ALOHA, length=Nstations, westmostlon=0)
10-element Array{OceanographyCruises.Station,1}:
 Station Sydney to ALOHA 1 (30.0S, 156.0E)
 
 Station Sydney to ALOHA 2 (24.1S, 161.1E)
 
 Station Sydney to ALOHA 3 (18.3S, 166.2E)
 
 Station Sydney to ALOHA 4 (12.4S, 171.3E)
 
 Station Sydney to ALOHA 5 (6.6S, 176.4E)
  
 Station Sydney to ALOHA 6 (0.7S, 181.6E)
  
 Station Sydney to ALOHA 7 (5.2N, 186.7E)
  
 Station Sydney to ALOHA 8 (11.0N, 191.8E)
 
 Station Sydney to ALOHA 9 (16.9N, 196.9E)
 
 Station Sydney to ALOHA 10 (22.8N, 202.0E)

(westmostlon=0 ensures that the longitudes are in (0,360) to match the OCIM1 grid we use here.)

We can now construct a fictitious cruise track

ct = CruiseTrack(name="CruisyMcCruiseFace", stations=stations)

and check the station locations by overlaying a plot of the cruise's track over a surface map of the dummy tracer

surfacemap(dummy, grd, color=:grays)
plotcruisetrack!(ct, markercolor=:red)
0 100 200 300 -75 -50 -25 0 25 50 75 Longitude Latitude - 0.75 - 0.50 - 0.25 0 0.25 0.50 0.75 1.00 CruisyMcCruiseFace

Let's create a transect of data that is almost equal to the dummy.

First, a function for creating random depths

function randomdepths(n, max)
    depths = cumsum(rand(n+1))
    return max * view(depths,1:n) / maximum(depths)
end
Nobs = rand(1:20, Nstations) # number of obs per station/profile
depths = [randomdepths(Nobs[i], 4000) for i in 1:Nstations]
obs = [[fdummy(st.lat, st.lon, d) .+ 0.1randn() for d in depths[i]] for (i,st) in enumerate(stations)]
profiles = [DepthProfile(station=st, depths=depths[i], values=obs[i]) for (i,st) in enumerate(stations)]

t = Transect(tracer="dummy", cruise=ct.name, profiles=profiles)

Transects

Zonal transect

We can plot the modelled dummy data along the ct cruise track in the zonal directiion (along longitudes) with

zonaltransect(dummy, grd, ct)
160 170 180 190 200 18 55 94 137 187 247 317 401 501 619 758 919 1104 1317 1559 1833 2141 2485 2867 3290 3756 4267 4825 5433 CruisyMcCruiseFace Longitude (°) Depth (m) 0 0.25 0.50 0.75 1.00 1.25 1.50 1.75 2.00 2.25

If we want the observations transect on top of it

zonalscattertransect!(t)
160 170 180 190 200 18 55 94 137 187 247 317 401 501 619 758 919 1104 1317 1559 1833 2141 2485 2867 3290 3756 4267 4825 5433 dummy along CruisyMcCruiseFace Longitude (°) Depth (m) 0 0.25 0.50 0.75 1.00 1.25 1.50 1.75 2.00 2.25

Meridional transect

Same for meridional transects (along latitude)

meridionaltransect(dummy, grd, ct)
-30 -20 -10 0 10 20 18 55 94 137 187 247 317 401 501 619 758 919 1104 1317 1559 1833 2141 2485 2867 3290 3756 4267 4825 5433 CruisyMcCruiseFace Latitude (°) Depth (m) 0 0.25 0.50 0.75 1.00 1.25 1.50 1.75 2.00 2.25

and

meridionalscattertransect!(t)
-30 -20 -10 0 10 20 18 55 94 137 187 247 317 401 501 619 758 919 1104 1317 1559 1833 2141 2485 2867 3290 3756 4267 4825 5433 dummy along CruisyMcCruiseFace Latitude (°) Depth (m) 0 0.25 0.50 0.75 1.00 1.25 1.50 1.75 2.00 2.25

If you have the GEOTRACESTools package installed and the GEOTRACES data installed at the right location, you can instead plot real data with something like

using GEOTRACESTools
zonalscattertransect(tracertransect("Fe", "GA02"))

However, this cannot be showcased online because GEOTRACES decided its data should "not be distributed to third parties".

Other plots

Plots the modelled ratio of two modelled tracers at a given station.

dummy1 = cosd.(latvec(grd)) + sqrt.(depthvec(grd)) / 30
dummy2 = cosd.(2latvec(grd)) + 0.5sqrt.(depthvec(grd)) / 30
ratioatstation(dummy1, dummy2, grd, ALOHA, xlabel="dummy 1", ylabel="dummy 2")
1.5 2.0 2.5 3.0 0.75 1.00 1.25 1.50 1.75 dummy 1 dummy 2 - 5000 - 4000 - 3000 - 2000 - 1000 depth [m] ALOHA

This can be useful to compare stoichiometric ratios at different stations.

ratioatstation!(dummy1, dummy2, grd, Sydney, marker=:square)
1.0 1.5 2.0 2.5 3.0 0.75 1.00 1.25 1.50 1.75 dummy 1 dummy 2 - 5000 - 4000 - 3000 - 2000 - 1000 depth [m] ALOHA Sydney

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